There exists an interest in classifying, tracking, and canceling the signals from military assets using passive acoustic sensors. Goals for battlefield acoustics include localization, tracking, identification, motion compensation/Autofocus. preprocessor, focus spectrum (classification algorithms, nulling algorithms, and small improvement localization algorithms). As to autofocus, phase gradient autofocus (PGA) algorithm is the subject of P. H Eichel. and C. V. Jakowatz, “Phase gradient algorithm as an optimal estimator of the phase derivative,” Optics Letters, Vol. 14, No. 20, 1101-1103, (1989) and P. H Eichel, D. C. Ghiglia, and C. V. Jakowatz, Jr., “Speckle processing method for synthetic aperture radar phase correction,” Optics Letters, Vol. 14, 1101-1103, (1989), both of which are hereby incorporated by reference.
During the classifying, tracking, and/or canceling of signals from military assets using passive acoustic sensors, many targets have acoustic signatures with large peaks in their spectrum that can be exploited by signal processing algorithms. However, target motion and turbulence in the atmosphere can distort the transmitted signal and degrade the performance of these signal processing algorithms. Preprocessing the data using motion compensation and autofocus algorithms can focus the signature of the target, and thereby provide longer coherent processing interval durations and improved performance of previously developed algorithms.